To enhance sensor capabilities, sensor data readings from different modalities must be fused. The main contribution of this paper is to present a sensor data fusion approach that can reduce KinectTM sensor limitations. This approach involves combining laser with KinectTM sensors. Sensor data is modelled in a 3D environment based on octrees using a probabilistic occupancy estimation. The Bayesian method, which takes into account the uncertainty inherent in the sensor measurements, is used to fuse the sensor information and update the 3D octree map. The sensor fusion yields a？significant increase of the field of view of the KinectTM sensor that can be used for robot tasks.
References
[1]
Wurm, K.M.; Hornung, A.; Bennewitz, M.; Stachniss, C.; Burgard, W. OctoMap: A Probabilistic, Flexible, and Compact 3D Map Representation for Robotic Systems. Proceedings of the ICRA 2010 Workshop on Best Practice in 3D Perception and Modeling for Mobile Manipulation, Anchorage, AK, USA, 3 May 2010.
[2]
de la Puente, P.; Rodriguez-Losada, D.; Valero, A.; Matia, F. 3D Feature Based Mapping Towards Mobile Robots' Enhanced Performance in Rescue Missions. Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '09), St. Louis, MO, USA, 11–15 October 2009; pp. 1138–1143.
[3]
Hokuyo. URG-04LX-UG01. Available online: http://www.hokuyo-aut.jp/02sensor/07scanner/urg04lxug01.html , accessed on 22 February 2012.
[4]
Agoston, M.K. Computer Graphics and Geometric Modelling Implementation and Algorithms; Springer: Berlin, Heidelberg, Germany, 2005.
[5]
Payeur, P.; Hebert, P.; Laurendeau, D.; Gosselin, C.M. Probabilistic Octree Modeling of a 3D Dynamic Environment. Proceedings of the IEEE International Conference on Robotics and Automation, Albuquerque, NM, USA, April 1997. Volume 2; pp. 1289–1296.
[6]
Wilhelms, J.; Gelder, A. Octrees for faster isosurface generation. IEEE Trans. Med. Imag. 2000, 19, 739–758, doi:10.1109/42.875199.
[7]
Wurm, K.; Hennes, D.; Holz, D.; Rusu, R.; Stachniss, C.; Konolige, K.; Burgard, W. Hierarchies of Octrees for Efficient 3D Mapping. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '11), San Francisco, CA, USA, 25–30 September 2011.
[8]
Donald, M. Geometric modeling using octree encoding. Comput. Graph. Image Process 1982, 19, 129–147, doi:10.1016/0146-664X(82)90104-6.
[9]
Moravec, H.; Elfes, A. High Resolution Maps from Wide Angle Sonar. Proceedings of the 1985 IEEE International Conference on Robotics and Automation, St. Louis, MO, USA, 25–28 March 1985. Volume 2; pp. 116–121.
[10]
Thrun, S.; Fox, D.; Burgard, W. Probabilistic Robotics; MIT Press: Cambridge, MA, USA, 2005.
[11]
Moravec, H.P. Sensor fusion in certainty grids for mobile robots. AI Mag. 1988, 9, 61–74.
[12]
Openni. Available online: http://75.98.78.94/default.aspx , accessed on 22 February 2012.
[13]
Kinect Matlab. Available online: http://www.mathworks.com/matlabcentral/fileexchange/30242 , accessed on 22 February 2012.
[14]
URG programming guide. Available online: http://www.hokuyo-aut.jp/02sensor/07scanner/download/urgprogramsen/ , accessed on 22 February 2012.
